Metadata-Version: 2.1
Name: pylazaro
Version: 1.0.8
Summary: A Python library for detecting lexical borrowings (with a focus on anglicisms in Spanish language)
Home-page: https://pylazaro.readthedocs.io/
Author: Elena Álvarez Mellado
Author-email: ealvarezmellado@gmail.com
License: MIT
Description: # pylazaro
        A library for lexical borrowing detection (a.k.a loanwords) in Spanish, with a focus on anglicism detection.
        
        ### Installation
        To install `pylazaro` simply run the following command from the command line: 
        
        ```
           pip install pylazaro
           ```
        
        To uninstall `pylazaro` simply run the following command from the command line:    
        ```
           pip uninstall pylazaro
           ```
        
        ### Get started
        A working example on how to detect borrowings in a text using `pylazaro`:
        
        ```
        >>> from pylazaro import Lazaro
        
        # We create our borrowing detection tagger
        >>> tagger = Lazaro()
        
        # The text we want to analyze for borrowing detection
        >>> text = "Inteligencia artificial aplicada al sector del blockchain, la e-mobility y las smarts grids entre otros; favoreciendo las interacciones colaborativas."
        
        # We run our tagger on the text we want to analyze
        >>> result = tagger.analyze(text)
        
        # We get results
        >>> result.borrowings()
        [('blockchain', 'ENG'), ('e-mobility', 'ENG'), ('smarts grids', 'ENG')]
        
        >>> result.tag_per_token()
        [('Inteligencia', 'O'), ('artificial', 'O'), ('aplicada', 'O'), ('al', 'O'), ('sector', 'O'), ('del', 'O'), ('blockchain', 'B-ENG'), (',', 'O'), ('la', 'O'), ('e-mobility', 'B-ENG'), ('y', 'O'), ('las', 'O'), ('smarts', 'B-ENG'), ('grids', 'I-ENG'), ('entre', 'O'), ('otros', 'O'), (';', 'O'), ('favoreciendo', 'O'), ('las', 'O'), ('interacciones', 'O'), ('colaborativas', 'O'), ('.', 'O')]
        ```
        
        ### More info 
        * Documentation on how to use `pylazaro` in [Read the docs](https://pylazaro.readthedocs.io/).
        * The code is available on [GitHub](https://github.com/lirondos/pylazaro).
        * `pylazaro` gives access to the models described on [this ACL paper](https://aclanthology.org/2022.acl-long.268/)
        * Questions? Bugs? Requests? Ideas? Feel free to reach me [via email](mailto:ealvarezmellado@gmail.com), open [a GitHub issue](https://github.com/lirondos/pylazaro/issues) or ping me [on Twitter](https://twitter.com/lirondos).
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
